INS and GNSS fusion enhancement based on a weighted reliabilities approach

Alexandre Patarot, Mehdi Boukallel, Sylvie Lamy-Perbal, Alexandre Vervisch-Picois, Nel Samama

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The maturity of outdoor positioning systems based on satellites encourages indoor positioning research to focus on radio technologies. However, specific infrastructures often have to be deployed in this case. Then, inertial sensors appear to be a good relay to radio systems. A system fusing INS and GNSS could thereby compute a position anywhere. Yet, taking advantage of each sensor requires to know which one is the most reliable in real-time. Therefore, a quantification of the sensors' reliabity is introduced in this paper. This approach aims at running both outdoors and indoors. Moreover, the complexity of algorithms is carefully studied here to fit the user mobility requirements. Experiments are conducted in reproducible situations and results show that taking reliabilities into account benefits the hybridization of INS and GNSS for positioning in both convenient and constrained environments.

Original languageEnglish
Title of host publication2012 International Conference on Indoor Positioning and Indoor Navigation, IPIN 2012 - Conference Proceedings
PublisherIEEE Computer Society
ISBN (Print)9781467319546
DOIs
Publication statusPublished - 1 Jan 2012
Externally publishedYes
Event2012 International Conference on Indoor Positioning and Indoor Navigation, IPIN 2012 - Sydney, NSW, Australia
Duration: 13 Nov 201215 Nov 2012

Publication series

Name2012 International Conference on Indoor Positioning and Indoor Navigation, IPIN 2012 - Conference Proceedings

Conference

Conference2012 International Conference on Indoor Positioning and Indoor Navigation, IPIN 2012
Country/TerritoryAustralia
CitySydney, NSW
Period13/11/1215/11/12

Keywords

  • Hybrid positioning
  • INS (Inertial Navigation System) and GNSS (Global Navigation Satellite System) Fusion
  • Pedestrian Navigation
  • Weighted Reliabilities

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